Risk-Based Monitoring. Risk-Based Execution. Risk-Based Quality Management. The monitoring and management of clinical trials are called many things—yet, they are, in fact, different. FDA Director of the Office of Scientific Investigations, David Burrow, notes that “Risk-based quality management is not just risk-based monitoring.” RBQM is a more substantial undertaking, requiring quality, reliability, and interpretability. It is achieved through a combination of risk assessment, appropriate protocols, and risk-based monitoring. And to be successfully implemented, it demands planning, based on proper assessments, with mitigation, escalation, and remediation strategies. Regulators want to see clinical trials implementing this approach. Yet, sponsors and contract research organizations (CROs) are finding it challenging. It doesn’t have to be.
There is a considerable shift in the volume, the sources, and the complexity of data.
Today, we live in the new world of Big Data. Indeed, the largest companies on the planet are data companies, and they ensure that we generate new data at every moment, which they then accrue, analyze, and utilize. This data explosion has also occurred within clinical trials, as we gather information from an increasing diversity of laboratory assays, from wearable devices, from electronic health records—and even from banks of historical data. Yet the ability to harness all that clinical trial data has not kept pace. As these sources of data continue to multiply, shift, and evolve, we face an increasing imperative to take a fresh approach to clinical trial data management.
It’s time for the clinical trial industry to leave legacy technologies and processes behind.
The technology used in dozens of industries has evolved to manage, analyze, and react to multiple data points in near real-time. Think of the fraud alerts triggered by atypical credit card expenditures or the various interconnected processes involved in using the Uber app.
Yet the clinical trial industry lags, mainly using technologies developed in the 1970s and 1980s. They are inadequate for today’s needs. Like Uber passengers, the industry would benefit from a single application that could manage extensive data and complex processes in one seamless, easy-to-use interface that boils down to a single, simple question when you log in: Where to?
Instead, most people are still using legacy Clinical Trial Management Systems (CTMS) that were initially created by uniting many disparate technologies under a single centralized umbrella system. As they have grown more complex, individual capabilities have split off, so now a trial may have separate portals for investigative management, for payments, for contacts. Most CTMSs do not have built-in analytics tools; those need to be managed separately.
Meanwhile, despite the onslaught of data, monitoring processes remain mostly unchanged. Now, instead of conducting a 100% source data verification (SDV) by comparing paper case report forms against medical records, monitors compare the electronic data capture to the medical history. This still occurs in person at the study site.
New technologies can simplify trial monitoring and management while delivering more accurate results.
Clinical trials are designed to ensure safety and measure the efficacy of potential new therapeutics. They do so by collecting, monitoring, and analyzing data. It is imperative both to eliminate any fraudulent data and to confirm that all the collected data is accurate and complete. Yet, the massive new amounts of data have made that increasingly challenging and legacy monitoring processes, such as SDV, have proven inadequate for capturing errors. Regulators and industry experts are seeking change.
- In the design phase of every study, thoughtful consideration should be given to whether monitoring will be onsite, remote, or centralized—and why.
- The operation and management of clinical trial data should occur on one consolidated platform that guides the user through the process and provides actionable outputs.
- That data should be accessible and useable in day-to-day trial operations—both onsite and remote.
This software should not require manual engagement, and it should not merely move current processes online. It should revolutionize the steps themselves, offering true integration, simplification, and speed.
It is possible to combine business intelligence tools and operational systems. Demand it.
RBQM should be the foundational approach to managing a study. Through continual, ongoing evaluation, it improves the data quality and therefore improves both analysis and the capture of safety issues. It also enhances the efficiency of the study manager or clinical research associate.
That’s because RBQM isn’t complicated—and the right technology can make RBQM virtually simple.
By integrating all systems into a single platform, sponsors and CROs can deliver consistency across monitoring roles, essential for a regulatory audit trail. They can also build efficiencies within the system to produce more accurate results faster and with some potential cost-savings. They can bring clinical trial monitoring and management into the twenty-first century. To learn more about the technology divide and how to solve it, we invite you to check out our webinar, Sharp Thinking: A New Angle on Clinical Trial Management Systems.